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. 2025 Aug 16.
doi: 10.1245/s10434-025-18040-y. Online ahead of print.

Evaluation of Diagnostic Accuracy of Preoperative CT-Based Radiomics in Primary Retroperitoneal Sarcoma

Fabio Tirotta  1 , Anne-Rose W Schut  2 , Demi Wemmers  2 , Stefan Klein  3 , Jacob J Visser  4 , David F Hanff  4 , Marielle Olsthoorn  4 , Dirk J Grünhagen  2 , Geert J L H van Leenders  5 , Winan J van Houdt  6 , Cornelis Verhoef  2 , Martijn P A Starmans  3   5
Affiliations

Evaluation of Diagnostic Accuracy of Preoperative CT-Based Radiomics in Primary Retroperitoneal Sarcoma

Fabio Tirotta et al. Ann Surg Oncol. .

Abstract

Background: Obtaining an accurate preoperative diagnosis in retroperitoneal sarcoma (RPS) is challenging, and radiomics-based models may offer a valid option to achieve this outcome. This study evaluated the accuracy of radiomics-based preoperative CT models at predicting tumour histology and grade in patients with primary RPS.

Methods: Data on consecutive patients who underwent surgery for primary retroperitoneal liposarcoma (RLPS) and leiomyosarcoma (RLMS) were analysed. Four different CT radiomics-based models were devised: 1) to distinguish between RLPS and RLMS; 2a) to predict overall tumour grade in both RLPS and RLMS; 2b and 2c) to predict tumour grade in RLPS and RMLS, respectively. The models were evaluated in a 100× random-split cross-validation.

Results: Data were available for 100 patients (64 RLPS, 36 RLMS), with 34 RLPS and 22 RLMS patients having a high-grade tumour on final histology. No significant differences in terms of age (p = 0.46), sex (p = 0.13), tumour location (p = 0.52), tumour diameter (p = 0.16), or tumour volume (p = 0.45) were observed between high- and low-grade tumours. The resulting area under the curve (AUC) at distinguishing between RLPS and RLMS was 0.94. The AUC at differentiating between high- and low-grade tumours for both RLPS and RMLS was 0.74. When tumour grade was analysed separately the corresponding AUC for RLPS and RLMS was 0.87 and 0.61, respectively.

Conclusions: Radiomics-based preoperative CT-models were demonstrated to be accurate at differentiating between RLMS and RLPS, and at predicting preoperative tumour grade in RLPS, whereas they performed poorly in RLMS.

Keywords: Leiomyosarcoma; Liposarcoma; Radiomics; Retroperitoneal sarcoma; Surgical oncology.

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Conflict of interest statement

Disclosures: Stefan Klein—Payment to institution: EuCanImage (European Union's Horizon 2020 research and innovation program under grant agreement number 952103). Jacob Visser—Grants to institution from Promedius/Enlitic/Qure.ai; Consulting fees from Philips (payment to institution); Leadership on the steering committee of the PINPOINT Project (payment to institution from AstraZeneca). Ethical Approval: Ethical approval was obtained by the Erasmus MC medical ethics committee (MEC-2020-0293).

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